Robotic manipulation in cluttered environments presents significant challenges, particularly when the clutter includes thin, deformable objects like cables, which complicate perception and decision-making processes. In the context of datacenters, the automation of networking tasks often involves the manipulation of optical transceivers within densely packed cable configurations. Such environments are characterized by an abundance of delicate, overlapping, and intersecting cables, leading to frequent occlusions. This paper introduces an innovative system designed for the manipulation of optical transceivers in environments cluttered by cables. Our integrated approach combines advanced 3D scene understanding with a heuristic-based pushing policy to effectively manipulate optical transceivers amidst clutter. The system's perception component utilizes image segmentation and 3D reconstruction to accurately model the transceivers and surrounding cables. Meanwhile, the planning aspect employs a search algorithm with task-specific heuristics, to navigate the gripper, displace obstructing cables, and safely achieve a precise pre-grasp position in front of the target transceiver. We have conducted extensive evaluations of our methodology in both simulated and real-world settings, demonstrating its high success rates, robustness, and proficiency in addressing the unique challenges posed by cable-occluded environments within datacenters.

Sustainable and cost-effective long-term storage remains an unsolved problem. The most widely used storage technologies today are magnetic (hard disk drives and tape). They use media that degrades over time and has a limited lifetime, which leads to inefficient, wasteful, and costly solutions for long-lived data. This article presents Silica: the first cloud storage system for archival data underpinned by quartz glass, an extremely resilient media that allows data to be left in situ indefinitely. The hardware and software of Silica have been co-designed and co-optimized from the media up to the service level with sustainability as a primary objective. The design follows a cloud-first, data-driven methodology underpinned by principles derived from analyzing the archival workload of a large public cloud service. Silica can support a wide range of archival storage workloads and ushers in a new era of sustainable, cost-effective storage.

The vision of self-maintaining systems is to make cloud hardware automatically servicing and repairing using robotics. We define a self-maintaining system as one where software can control robotics that can automatically perform hardware maintenance tasks and repair operations. This reduces failure service windows and lowers the risk of repairs causing further cascading failures and outages. Self-maintaining systems are not purely reactive to failures, but also do proactive maintenance before failures occur which reduces future hardware failures. Operating an entire datacenter as a self-maintaining system is many years away, and we present four stages of automation, analogous to levels used for autonomous vehicles, required to reach the full vision for datacenters.

Automated storage and retrieval systems (ASRS) are a key component of the modern storage industry, and are used in a wide range of applications, carrying anything from lightweight tape cartridges to entire pallets of goods. Many of these systems are under pressure to maximise the use of space by growing in height and density, but this can create challenges for the the robots that service them. In this context, we present RASCAL, a novel ASRS robot for small payload items in structured environments, with a focus on system-level scalability and redundancy. We describe the design objectives of RASCAL and how they address some of the limitations of existing robotic systems in this area, such as scalability and redundancy. We then demonstrate the viability of our design with a proof-of-concept implementation of a data centre storage media robot, and show through a series of experiments that its design, speed, accuracy, and energy efficiency are appropriate for this application.

Sustainable and cost-effective long-term storage remains an unsolved problem. The most widely used storage technologies today are magnetic (hard disk drives and tape). They use media that degrades over time and has a limited lifetime, which leads to inefficient, wasteful, and costly solutions for long-lived data. This paper presents Silica: the first cloud storage system for archival data underpinned by quartz glass, an extremely resilient media that allows data to be left in situ indefinitely. The hardware and software of Silica have been co-designed and co-optimized from the media up to the service level with sustainability as a primary objective. The design follows a cloud-first, data-driven methodology underpinned by principles derived from analyzing the archival workload of a large public cloud service. Silica can support a wide range of archival storage workloads and ushers in a new era of sustainable, cost-effective storage.